INET 4062

About This Course

This course is a follow-up to INET 4061 – Data Science I: Machine Learning Fundamentals. It covers the tools required to apply and implement data science techniques such as mathematical programming libraries, cloud resources, and big data databases. It also gives an overview of advanced data science methodologies such as deep learning, reinforcement learning, recommendation systems, and linear programming.

Sample course topics: Python and Spark, Common ML algorithms/workflow, operations, and platforms; cloud computing; big data database systems; neural networks; computer vision and natural language processing; recommender systems; reinforcement learning; optimization.

Prerequisites: Basic programming knowledge (Java, Python, R). Linear algebra and calculus strongly recommended (e.g., MATH 2243 and 2263). INET 4061 strongly recommended.

Instructors

Head shot of Ian-Mathew Hornburg
Ian-Mathew Hornburg

BASc, Information Technology Infrastructure, University of Minnesota

Ian-Mathew's work focuses on the development of resilient big data infrastructure, large-scale data engineering, and its application in data science. His expertise includes infrastructure, software engineering, and risk management in the finance and retail sectors. He has also served as an enterprise technical manager of open-source software and platforms used for data science and analysis. Ian-Mathew values building effective engineering cultures in teams and foregrounding ethical considerations in the development and deployment of technology. He also has more than a decade of small-team leadership experience as a veteran of the US Army and is an active contributor to initiatives to make tech more inclusive and accessible for all.

  • INET 2001 – Fundamentals of IT
  • INET 4061 – Data Science I: Machine Learning Essentials
  • INET 4062 – Data Science II: Advanced Analytics and AI
Eric DeClouet
Eric DeClouet

MBA with emphasis in operations management and finance, University of Pittsburgh, Katz Graduate School of Business; BS, physics, University of Pittsburgh

Eric DeClouet is a seasoned IT professional with a diverse background and over two decades of experience leading IT initiatives across many sectors (retail, financial services, healthcare, manufacturing, and consulting) and leadership roles at companies like Medtronic, 3M, BestBuy, Ameriprise, Allianz, Inovalon, and UnitedHealth. With broad technical expertise (portfolio management, enterprise architecture, data management, integration, virtualiztion) and business acumen (finance, manufacturing, logistics, healthcare). Eric is adept at "teaching through analogy," i.e., tackling the challenge of embracing the new by using analogies to what's familiar in the learner's background.

  • INET 4062 – Data Science II: Advanced Analytics and AI

Information Subject to Change

Course details, syllabus, and instructor are subject to change. Current course details can be found by clicking on the Term link(s) above.